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Measure and improve Three.js or WebGL game performance through repeatable gameplay checks. Identify CPU or GPU bottlenecks, reduce unnecessary rendering and processing, and verify that controls, collisions, visuals, and memory remain stable.
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Review Apache Pinot changes affecting frequently executed code or making performance claims in a pull request. Relevant areas include operators, segment readers, aggregation functions, and locking inside loops that process individual rows.
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Write, review, and refactor React and Next.js code using Vercel's performance guidelines. Apply prioritized rules to reduce sequential data fetching, shrink downloaded code, improve server processing, and avoid unnecessary updates to the interface.
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Interpret MSBuild performance summaries when ResolveProjectReferences appears unusually expensive. Separate time spent waiting for dependent projects from actual task work, then use task self-time rankings to identify a concrete optimization target.
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Choose diagnostic tools and collect performance traces for production .NET problems such as high CPU usage, memory growth, or slow requests. Get environment-specific collection commands and guidance on which tools to use for later analysis.
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Analyze MSBuild binary logs and timing summaries to find why builds are slow. Identify costly reference resolution, code analysis, file copying, restore work, or serialized tasks, then prioritize improvements by their share of total build time.
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Establish repeatable performance measurements for MSBuild and .NET builds before optimizing. Compare clean-output, changed-source, and unchanged builds, record timing ranges, and assess output layouts, dependency references, and parallel build options against the measured baseline.
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Compare Google and Meta campaign results across mobile, desktop, and tablet. Identify device performance gaps, investigate whether ads, landing pages, or audiences explain them, and receive recommendations for bids, campaign splits, and page changes.
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Guides performance improvements when writing, reviewing, or refactoring React and Next.js applications. Prioritized rules cover data fetching, bundle size—the amount of code delivered to browsers—and rendering, with explanations and code examples.
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Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.
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Profile JAX, Levanter, or Marin training to investigate slow startup, compilation, initialization, or throughput. Turn execution traces, recorded timing events, into structured reports, identify costly operations, and compare performance before and after a bounded change.
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Investigate slow interactions and rendering using performance traces, which record execution events, alongside source code. Identify the responsible code, distinguish measurements from hypotheses, and guide fixes that preserve behavior, with tests and comparable recordings for verification.
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Choose the appropriate NVSHMEM performance workflow for collecting benchmark evidence, selecting communication between nodes, assigning network adapters to processing elements, or assessing TMA transfers between peer GPUs. This skill routes requests to specialists that perform the technical work.
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Diagnose slow loading, high memory use, and low frame rates in USD 3D scenes. It coordinates measurement, scene validation, and optimization, then produces reports comparing available before-and-after evidence and an optimized scene when changes are performed.
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Build and run the GPUNetIO benchmark to measure sustained RDMA WRITE bandwidth, a remote-memory transfer rate driven by a CUDA kernel. Interpret results, investigate run-to-run variation, and identify GPU, network adapter, or link bottlenecks.
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Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (→ See `samber/cc-skills-golang@golang-benchmark` skill) or debugging workflow (→ See `samber/cc-skills-golang@golang-troubleshooting` skill).
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[omh] Software slowness, memory leaks, or cost spikes: find where a system is actually slow, leaking, or expensive across runtime, memory, token cost, storage, rendering, inference, CI, and query domains, then fix one measured hot path at a time behind a regression budget. Use when the user says: ultraperf, ulw-perf, performance audit, performance bottleneck, find the bottleneck, profile the hot path, memory leak investigation, token cost hotspot.
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Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges.
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HyperFrames CLI tool — hyperframes init, lint, preview, render, transcribe, tts, doctor, browser, info, upgrade, compositions, docs, benchmark. Use when scaffolding a project, linting or validating compositions, previewing in the studio, rendering to video, transcribing audio, generating TTS, or troubleshooting the HyperFrames environment.
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Install and wire registry blocks and components into HyperFrames compositions. Use when running hyperframes add, installing a block or component, wiring an installed item into index.html, or working with hyperframes.json. Covers the add command, install locations, block sub-composition wiring, component snippet merging, and registry discovery.
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Web performance measurement and debugging toolkit. Use when the user asks about web performance, wants to audit a page, or says "analyze performance", "debug lcp", "check ttfb", "measure core web vitals", "audit images", or similar.
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Audit and prioritize performance work through bounded-work and forward-progress checks. Use when asked to find performance issues, investigate freezes/500s/OOMs, review retries or polling for no-progress loops, rank a performance backlog, or implement the next simple performance fixes.
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Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure execution time with statistical rigor, or use runperf.
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Install, discover, and wire registry blocks and components into HyperFrames compositions. Use when running hyperframes add or hyperframes catalog, installing one item or every block matching a tag, wiring an installed item into index.html, or working with hyperframes.json. Covers discovery, install locations, block sub-composition wiring, component snippet merging, and authoring a new block or component to contribute upstream (idea → scaffold → validate → PR).
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